Beyond Markowitz with multiple criteria decision aiding

The paper is about portfolio selection in a non-Markowitz way, involving uncertainty modeling in terms of a series of meaningful quantiles of probabilistic distributions. Considering the quantiles as evaluation criteria of the portfolios leads to a multiobjective optimization problem which needs to be solved using a Multiple Criteria Decision Aiding (MCDA) method. The primary method we propose for solving this problem is an Interactive Multiobjective Optimization (IMO) method based on so-called Dominance-based Rough Set Approach (DRSA). IMO-DRSA is composed of two phases: computation phase, and dialogue phase. In the computation phase, a sample of feasible portfolio solutions is calculated and presented to the Decision Maker (DM). In the dialogue phase, the DM indicates portfolio solutions which are relatively attractive in a given sample; this binary classification of sample portfolios into ‘good’ and ‘others’ is an input preference information to be analyzed using DRSA; DRSA is producing decision rules relating conditions on particular quantiles with the qualification of supporting portfolios as ‘good’; a rule that best fits the current DM’s preferences is chosen to constrain the previous multiobjective optimization in order to compute a new sample in the next computation phase; in this way, the computation phase yields a new sample including better portfolios, and the procedure loops a necessary number of times to end with the most preferred portfolio. We compare IMO-DRSA with two representative MCDA methods based on traditional preference models: value function (UTA method) and outranking relation (ELECTRE IS method). The comparison, which is of methodological nature, is illustrated by a didactic example.     

Bayesian Reanalysis of the Challenger O-Ring Data

A Bayesian forecasting model is developed to quantify uncertainty about the postflight state of a field-joint primary O-ring (not damaged or damaged), given the O-ring temperature at the time of launch of the space shuttle Challenger in 1986. The crux of this problem is the enormous extrapolation that must be performed: 23 previous shuttle flights were launched at temperatures between 53 °F and 81 °F, but the next launch is planned at 31 °F. The fundamental advantage of the Bayesian model is its theoretic structure, which remains correct over the entire sample space of the predictor and that affords flexibility of implementation. A novel approach to extrapolating the input elements based on expert judgment is presented; it recognizes that extrapolation is equivalent to changing the conditioning of the model elements. The prior probability of O-ring damage can be assessed subjectively by experts following a nominal-interacting process in a group setting. The Bayesian model can output several posterior probabilities of O-ring damage, each conditional on the given temperature and on a different strength of the temperature effect hypothesis. A lower bound on, or a value of, the posterior probability can be selected for decision making consistently with expert judgment, which encapsulates engineering information, knowledge, and experience. The Bayesian forecasting model is posed as a replacement for the logistic regression and the nonparametric approach advocated in earlier analyses of the Challenger O-ring data. A comparison demonstrates the inherent deficiency of the generalized linear models for risk analyses that require (1) forecasting an event conditional on a predictor value outside the sampling interval, and (2) combining empirical evidence with expert judgment.     

The link between parenting approaches and health behavior: A systematic review

The familial home environment, where parenting takes place, plays an important role in the health behaviors that children and adolescents engage in and has implications on health and well-being in later life. Lifestyle-related behaviors predispose children and adolescents to the global burden of non-communicable and other lifestyle-related diseases. This review therefore examined and described previous studies looking at the associations between health behaviors and parenting approaches. It suggests that engagement in health behaviors, which promotes overall health and well-being, was associated with autonomy, supportive parenting, parental encouragement, behavior control, parental nurturance, warmth and responsiveness, and parental involvement. The review highlights the gap in literature focusing on the health behavior of children and adolescents as well as on parenting. In addition, the review also provides an overview of the continents where fewer studies have examined the presented associations. The findings presented also serve as a guide for program development and implementation to address the increase in non-communicable and other lifestyle-related diseases.     

Safety and Solidarity After the Boston Marathon Bombing: A Comparison of Three Diverse Boston Neighborhoods

This article investigates the effect of the Boston Marathon Bombing on city residents— how the tragic incident changed, or did not change, how Bostonians live in and feel about their community and neighborhoods. Unlike prior research that began weeks or months after a terrorist attack and used retrospective reports, this study spans the focal event. An address‐based sample of residents from three neighborhoods, distinct in racial and economic makeup was surveyed by mail using a three‐contact protocol. About two‐thirds of respondents answered a survey of neighborhood sentiments, and health and well‐being in the days before the bombing (N = 581) and slightly over a third answered the survey after the bombing (N = 313). Assessments of safety, city and neighborhood satisfaction and solidarity, mental health, and other key measures vary greatly between the three neighborhoods, which are diverse in racial and economic composition, but also vary in proximity to the bomb site. Net of neighborhood differences, the bombing had a strong negative effect on neighborhood cohesion and reduced use of public transit. Strong interactions are also found between timing of survey completion (pre and post bombing) and neighborhood for assessments of neighborhood solidarity.     

Interval shrinkage estimators

This paper considers estimation of an unknown distribution parameter in situations where we believe that the parameter belongs to a finite interval. We propose for such situations an interval shrinkage approach which combines in a coherent way an unbiased conventional estimator and non-sample information about the range of plausible parameter values. The approach is based on an infeasible interval shrinkage estimator which uniformly dominates the underlying conventional estimator with respect to the mean square error criterion. This infeasible estimator allows us to obtain useful feasible counterparts. The properties of these feasible interval shrinkage estimators are illustrated both in a simulation study and in empirical examples.     

Can groups solve the problem of over-bidding in contests?

This study reports an experiment that examines whether groups can better comply with theoretical predictions than individuals in contests. Our experiment replicates previous findings that individual players significantly overbid relative to theoretical predictions, incurring substantial losses. There is high variance in individual bids and strong heterogeneity across individual players. The new findings of our experiment are that groups make 25% lower bids, their bids have lower variance, and group bids are less heterogeneous than individual bids. Therefore, groups receive significantly higher and more homogeneous payoffs than individuals. We elicit individual and group preferences toward risk using simple lotteries. The results indicate that groups make less risky decisions, which are possible explanations for lower bids in contests. Most importantly, we find that groups learn to make lower bids from communication and negotiation between group members.